Search Results - (( course evaluation ((from algorithm) OR (tree algorithm)) ) OR ( a simulation model algorithm ))*

Tracking student performance in introductory programming by means of machine learning by Khan I., Al Sadiri A., Ahmad A.R., Jabeur N.

An artificial intelligence approach to monitor student performance and devise preventive measures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

“…This research evaluates the effectiveness of machine learning algorithms to monitor students� academic progress and informs the instructor about the students at the risk of ending up with unsatisfactory result in a course. …”

Deep learning-based recommendation system to address challenges in providing electronic services by AL Hinai, Turki Abdullah Masood, Al Kulaibi, Juma, Al Husaini, Mohammed Abdulla Salim, Al Husaini, Yousuf Nasser, Habaebi, Mohamed Hadi

“…This study proposes an advanced academic performance prediction system using a Support Vector Machine (SVM) model, trained on a comprehensive dataset from 1,734 university students enrolled in the Spring 2024 semester. …”
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A Systematic Approach to Transform Machine Learning Students� Performance Prediction Model into Preventive Procedures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

“…The dataset is pre-processed with Pearson correlation feature selection algorithm to discover the features which influence the students� academic performance. …”

Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah by Nurul Habibah, Abdul Rahman

“…Drawing from a dataset spanning students enrolled in the Business Statistics course at Universiti Islam Pahang Sultan Ahmad Shah from 2013 to 2022, this study identifies students’ carry marks as the most correlated factor in determining performance levels. …”
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Leveraging data lake architecture for predicting academic student performance by Abdul Rahim, Shameen Aina, Sidi, Fatimah, Affendey, Lilly Suriani, Ishak, Iskandar, Nurlankyzy, Appak Yessirkep

“…In addition to forecasting the student performance, appropriate machine learning algorithms such as Support Vector Classifier, Naive Bayes, and Decision Trees are used to build prediction models by using the data lake's scalability and parallel processing capabilities. …”
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DurianCare: optimising trunk disease detection and precision farming in a mobile application / Muhammad Haziq Azmi by Azmi, Muhammad Haziq

“…The project will implement automated detection and disease management recommendation algorithms while evaluating the functionality and usability of the designed application. …”
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Assessing the simulation performances of multiple model selection algorithm by Yusof, Norhayati, Ismail, Suzilah, Tuan Muda, Tuan Zalizam

“…The capability of the algorithm in finding the true specification of multiple models is measured by the percentage of simulation outcomes.Overall results show that the algorithm has performed well for a model with two equations.The findings also indicated that the number of variables in the true models affect the algorithm performances. …”
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Using algorithmic taxonomy to evaluate lecturer workload by Hashim, Ruhil Hayati, Abdul Hamid, Jamaliah, Selamat, Mohd Hasan, Ibrahim, Hamidah, Abdullah, Rusli, Mohayidin, Mohd Ghazali

“…The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset. Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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A Model for Evaluation of Cryptography Algorithm on UUM Portal by Norliana, Abdul Majid

“…The purpose of this project are to construct and provide guidelines to develop a simulation model to evaluate cryptography algorithm in terms of encryption speed and descryption speed on UUM portal. …”
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Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation by Chang, Jan Voon

“…The main objective of this research is to validate the NIRR algorithm by developing a comprehensive simulation model using Discrete Event Simulation (DES). …”
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Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error as compared to a model with single learning algorithm.…”
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Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation by Chang, Jan Voon, Ahmad, Idawaty

“…The main objective of this research is to validate the NIRR algorithm by developing a comprehensive simulation model using Discrete Event Simulation (DES). …”
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Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal by Abdul Hamid, Jamaliah, Mohayidin, Mohd Ghazali, Selamat, Mohd Hasan, Ibrahim, Hamidah, Abdullah, Rusli, Hashim, Ruhil Hayati

“…The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset. Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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Incorporating the range-based method into GridSim for modeling task and resource heterogeneity by Eng, Kailun, Muhammed, Abdullah, Mohamed, Mohamad Afendee, Hasan, Sazlinah

“…In this paper, we propose a new simulation model that incorporates the range-based method into GridSim for modeling and simulating heterogeneous tasks and resources in order to capture the inherent heterogeneity of Grid environments that later can be used by other researchers to test their algorithms.…”
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Performance of Semi Active Lateral Control (SALC) algorithm for semi active suspension system in multibody co-simulation method / M. M. Abdul Majid ...[et al.] by Abdul Majid, M. M., Salleh, M. S., Abu Hashim, M. A., Ismail, N. H., Mansor, S., Abu Bakar, S. A.

“…Thus limiting benefits on handling characteristic with current available algorithms. The research scope covered experimental measurements, simulation model correlation, and vehicle plant modelling using multibody approach (MSC Adams/Car), controller algorithm development in Matlab/Simulink and performance validation in co-simulation environment. …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

“…A data parallel algorithm (DPA-EHD) is designed and implemented for the EHD equations. …”
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Power Delivery Network Modeling And Simulation By Using Delaunay-Voronoi Triangulation And The Latency Insertion Method by Chin, Wei Chun

“…The research is focused into the analysis of PDN by modeling and simulation of the power plane. In the project, power plane is modeled using Delaunay-Voronoi algorithm and for simulation, a fast transient simulation algorithm which is latency insertion method (LIM) is applied. …”
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Simulation Model and Genetic Algorithm to Assembly Line Balancing by Ali, A. J. Adham, Ahmad Nazif, Noor Kamar, Abdullah, Ibrahim, Sorooshian, Shahryar

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Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal by Abdul Hamid, Jamaliah, Mohayidin, Mohd Ghazali, Selamat, Mohd Hassan, Ibrahim, Hamidah, Abdullah, Rusli, Hashim, Ruhil Hayati

“…Lecturer workload at universities includes three major categories: teaching, research and services.Teaching workload is influence by various factors such as level taught courses, number of student, credit and contact hour and off campus or on campus course design.The UPM has a KM Portal that contains sets of metadata on lecturer profile and knowledge assets.The Lecturer profile contains information lecturer teaching, research, publication and many more.We constructed an algorithmic taxonomy based at the lecturer profile data to measure lecturer teaching workload.This method measures the lecturer teaching workload.The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset.Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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